Instructions to use Bootoshi/booking-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Bootoshi/booking-v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Bootoshi/booking-v1") prompt = "btcbooking with white skin and crowned round head and red cape in a jar" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: btcbooking with white skin and crowned round head and red cape in a jar
output:
url: images/image1.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: btcbooking with white skin and crowned round head and red cape
license: mit
btcboo king

- Prompt
- btcbooking with white skin and crowned round head and red cape in a jar
Trigger words
You should use btcbooking with white skin and crowned round head and red cape to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.